
Small Molecule Discovery
Widen your design options. Narrow down what to test.
01 · Researchers' pain points
Find clues to long-standing questions with Small Molecule Discovery

Hyper Screening X
Find synthesizable novel hits in a 160-trillion-compound virtual library, and get synthesis quotes too.
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Hyper Design
Add or replace R-groups to get up to 50 novel derivatives for each substitution site.
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Hyper Binding
Predicts drug–target binding in under 30s with PIGNet, our in-house physics-based deep-learning model, with 2.2× higher binding prediction accuracy than conventional physics-based models.
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Hyper Binding Co-folding
Predicts binding structures from just a protein name and ligand SMILES, even for targets without experimental structures.
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Meet your co-scientist
FAQ
Can I run analyses without any coding experience?
Yes — no coding required.
You don’t need to know Linux, R, or Python.
Simply upload your data through the web interface and request analysis strategies via AI chat.
From execution to interpretation, the entire process is handled automatically.
How is this different from ChatGPT or Gemini?
Will my data be used to train AI models?
Who owns the figures generated on this platform?
How is customer data protected?

